Persistent Scatterer InSAR Technique Research Articles

GROUND DEFORMATION MONITORING OF RECLAIMED LANDS ALONG MANILA BAY FREEPORT ZONE USING PS-INSAR TECHNIQUE

Abstract. In response to escalating land demands, land reclamation plays a vital role, but this comes with the challenge of ground deformations that threaten livelihoods and safety. To address the growing concern, Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is utilized. This remote sensing method is known for its cost-effectiveness, efficiency, and high-resolution capabilities, to monitor vertical ground deformations in Manila Bay Freeport Zone's reclaimed areas. Through adaptation and implementation of PS-InSAR via SARPROZ, measurements along the satellite’s line-of-sight (LOS) is integrated both for ascending and descending geometries using the Nearest Neighbor Vector (NNV) approach to decompose and derive precise vertical displacement values. Correlation analysis with annual leveling data from six benchmarks reveals a strong relationship with correlation coefficient > 0.80. The results indicate relative stability with localized subsidence due to differential settlement and nearby construction. The results from the PS-InSAR technique show that ground deformation on reclaimed lands is expected to continue. Hence, monitoring should be implemented to observe sustained settlements after reclamation, identify areas with significant deformations, detect building and structural deformations, and initiate solutions to reduce the risk of environmental hazards.

Assessment of Active Ground Subsidence in the Dibrugarh and Digboi Areas of Assam, Northeast India, Using the PSInSAR Technique

Ground deformation on a regional to local scale is the consequence of a wide range of natural processes such as tectonic and anthropogenic activities. Globally, the over-extraction of groundwater and hydrocarbon exploitation are the primary causes of ground subsidence. The current study demonstrates regional scale ground subsidence analysis of the Dibrugarh and Digboi regions of Brahmaputra alluvial plain, Assam, Northeast India. To understand the ongoing surface deformation satellite base, the RADAR technique has been applied using SENTINEL-1A data, which were acquired between 15 October 2015 to 25 January 2022. The assessment carried out via the time series analysis of the radar data suggests that the Dibrugarh area is subsiding at a rate of ~5 mm/yr, whereas the Digboi is deforming at a much faster rate (±22 mm/yr) than Dibrugarh. The presence of active faults in the subsurface and associated deformation is another reason for active ground subsidence. The outcomes of the current study validate that the study area is currently undergoing active subsurface deformation caused by both endogenic as well as exogenic processes. Furthermore, our Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) and satellite-based analysis suggest that the over-exploitation of the natural resources is enhancing the rate of deformation in the Brahmaputra alluvial plain in the northeast of India.

Satellite-based monitoring of an open-pit mining site using Sentinel-1 advanced radar interferometry: A case study of the December 21, 2020, landslide in Toledo City, Philippines

Understanding the causal factors and mechanisms behind catastrophic landslides and debris flows is crucial for accurate forecasting and disaster risk reduction. Synthetic aperture radar (SAR) data and interferometric SAR (InSAR) technologies provide valuable information for early warning systems’ landslide and debris flow detection and monitoring strategies. This paper applied the Sentinel-1 Persistent Scatterer InSAR (PSInSAR) technique to detect and monitor precursory slope movements over the open-pit mining site in Toledo City, Cebu Island, in the Philippines. The results show that the slope showed instabilities between December 30, 2019, to December 12, 2020, before the actual failure on December 21, 2020. The landslide initiation zone moved with velocities exceeding –10 mm/yr and reaching –90 mm/yr. The topography and morphology of the mining site contributed to the cut slope instabilities. The mining operations and hydrometeorological conditions during the analysis period aggravated the situation, leading to the cut slope failure. Overall, with favorable slope geometry, surface characteristics, and SAR data availability, the Sentinel-1 PSInSAR technique can serve as a landslide early warning system tool and aid decision-making in an actively operating open-pit mine and other landscapes.

Landslide Susceptibility Mapping Using Machine Learning Algorithm Validated by Persistent Scatterer In-SAR Technique.

Landslides are the most catastrophic geological hazard in hilly areas. The present work intends to identify landslide susceptibility along Karakorum Highway (KKH) in Northern Pakistan, using landslide susceptibility mapping (LSM). To compare and predict the connection between causative factors and landslides, the random forest (RF), extreme gradient boosting (XGBoost), k nearest neighbor (KNN) and naive Bayes (NB) models were used in this research. Interferometric synthetic aperture radar persistent scatterer interferometry (PS-InSAR) technology was used to explore the displacement movement of retrieved models. Initially, 332 landslide areas alongside the Karakorum Highway were found to generate the landslide inventory map using various data. The landslides were categorized into two sections for validation and training, of 30% and 70%. For susceptibility mapping, thirteen landslide-condition factors were created. The area under curve (AUC) of the receiver operating characteristic (ROC) curve technique was utilized for accuracy comparison, yielding 83.08, 82.15, 80.31, and 72.92% accuracy for RF, XGBoost, KNN, and NB, respectively. The PS-InSAR technique demonstrated a high deformation velocity along the line of sight (LOS) in model-sensitive areas. The PS-InSAR technique was used to evaluate the slope deformation velocity, which can be used to improve the LSM for the research region. The RF technique yielded superior findings, integrating with the PS-InSAR outcomes to provide the region with a new landslide susceptibility map. The enhanced model will help mitigate landslide catastrophes, and the outcomes may help ensure the roadway’s safe functioning in the study region.

Monitoring of construction-induced urban ground deformations using Sentinel-1 PS-InSAR: The case study of tunneling in Dangjin, Korea

The construction of underground tunnels can prime or trigger ground subsidence, and thus surface deformation monitoring is required during and post-construction. Freely available satellite data allow significant possibilities for the use of remote sensing techniques, particularly multi-temporal interferometric synthetic aperture radar (Mt-InSAR), for surface deformation monitoring. However, track records and field demonstrations of InSAR-based tunneling-related deformation monitoring are limited, particularly in identifying the spatiotemporal evolution of ground deformation and causal factors thereof from construction activities. Therefore, this study explores the feasibility of using satellite SAR data to monitor the surface deformation associated with different tunnel construction phases. Tunneling-related surface deformation was analyzed using the persistent scatterer InSAR (PS-InSAR) technique and Sentinel-1B SAR data; the PS-InSAR results were compared with those from the conventional leveling method. The velocity map of the study site revealed a localized subsidence trough associated with the construction of vertical shafts and shield tunneling. The cumulative time-series displacement map successfully tracked the spatial and temporal progression of ground deformations related to the phases of tunnel construction activities. The maximum subsidence rate in the radar line-of-sight direction was estimated to exceed 40 mm/yr, with maximum cumulative subsidence of ∼ 200 mm. The results clearly showed that dewatering during tunneling aggravated the subsidence phenomenon. The consequent compaction and consolidation of the compressible soil layers due to the lowered groundwater table were the main causes of subsidence. Our results demonstrate the viability of the PS-InSAR technique based on the C-band Sentinel-1 product as a monitoring method to examine the spatiotemporal evolution of ground deformation patterns during tunneling activities and as a possible preliminary surveying tool to identify ongoing abnormal settlement prior to tunnel construction.

Reconstruction of active surface deformation in the Rishi Ganga basin, Central Himalaya using PSInSAR: A feedback towards understanding the 7th February 2021 Flash Flood

Active surface deformation, displacement pattern, and erosional variability is estimated using the geomorphologically sensitive morphometry along with the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique using the Sentinel-1Adata (119 images) acquired between 07- 02-2017 and 10-02-2021. The average velocities for this dataset are estimated to be between ±11 mm/y. The Raunthi River catchment from where the flood was triggered is undergoing ~8 mm/y subsidence and ~10 mm/y uplift. Compared to this the basin wide deformation (Rishi Ganga basin) is estimated to be around ±10 mm/y with commulative ground displacement of around ±45 mm. The times series analysis suggests an increase in the ground displacement by around 5 mm/y and seems to be responsible for the expansion of pre-existing cracks in the vicinity of the Vaikrita Thrust (VT) and subsequent failure of the northern face of Nandi Peak on 7th February 2021. The Global Positioning System (GPS) derived strain distribution pattern indicate a relatively higher accumulation of strain (>0.35µ strain/y). The normalized steepness index (ksn) variation along the longitudinal section of Rishi Ganga and Raunthi River sub-basin in Central Himalayan region shows anomalous increase at the glacio-fluvial transitional processes. Moreover, the χ profiles as well as planform plots shows anomalously lower values within the Raunthi River sub-basin when compared with the Rishi Ganga basin. Based on the lower values of χ it is observed that Raunthi River sub-basin is undergoing high erosion which can be caused by the presence of sheared lithology and incision of the relict glacial and paraglacial sediments. We negate the suggestion that abrupt rise in the temperature was the major triggering mechanism for the recent disaster, instead it is the sheared lithology and pre-existing fissure developed because of differential uplift and subsidence in Raunthi River that led to the wedge failure and subsequent flash flood. Had the climate was the major driver of the recent tragedy ?, it should have impacted multiple hanging glaciers in the Rishi Ganga valley. Therefore, the study calls for detailed geomorphological, structural and glaciological investigation in regions dominated by glacial and paraglacial processes in the strategic regions of the Himalaya. Towards this, the state of art PSInSAR technique seems to provide fast and reliable detection of terrain instability/stability along with identification of potential areas of slope failures in near future in the glacial and preglacial zones.

Optimized landslide susceptibility mapping and modelling using PS-InSAR technique: a case study of Chitral valley, Northern Pakistan

Chitral valley lies in the eastern Hindu Kush range, one of the hotspot of landslide activities that leads to loss of lives and economy. Comprehensive landslide inventory and Landslide susceptibility provide the basic information to analyses and medicate the landslide activities which are not available for the area. Probabilistic and statistical methods have been using to develop susceptibility maps but limitations are countered to assess high accuracy. In this study Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique has been applied to estimate the slope deformation velocity (Vslope), which can be used to optimize the landslide susceptibility map for the study area. The frequency ratio and logistic regression models were applied for comparative assessment and to forecast the correlation between causative factors and landslide occurrence. Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) curve approach was used for accuracy comparison of both models which showed 75.45% and 85.61% accuracy for FR and LR respectively. LR method’s result was found superior and combined with the results of PS-InSAR to extract new Landslide Susceptibility Mapping (LSM) for the area which removed misclassifications in the results. This optimized susceptibility model will be helpful to mitigate the landslide disaster and provide support to authorities in the management of different development programs in the study area.

An Adaptive Phase Optimization Algorithm for Distributed Scatterer Phase History Retrieval

The multitemporal interferometric synthetic aperture radar (InSAR) technique based on distributed scatterers (DSs) has been widely applied in high-precision deformation measurements, which compensates for the drawback that the persistent scatterer InSAR technique does not obtain sufficient monitoring points, especially in rural areas. Considering that DS pixels are susceptible to various decorrelation factors, it is necessary to retrieve the optimal phase series by phase optimization algorithms (POAs). However, conventional POAs rely on a sample covariance matrix or complex coherence matrix (CCM) derived by spatially averaging statistically homogeneous pixel neighborhoods, which may blur and destroy phase information, especially in dense fringe areas. To overcome this limitation, an adaptive POA is proposed in this article. The adaptive POA artificially constructs a superior CCM by the filtered interferometric phase, which is derived through spatial adaptive filtering approach fusion of principal phase component estimation and fast nonlocal means filtering, and an accurate coherence matrix determined via coherence estimation bias correction. Moreover, the modified eigen-decomposition-based maximum-likelihood-estimator of the interferometric phase (EMI) with coherence-power-weighting is proposed to further improve the estimation precision and computational efficiency. The estimated CCM is then processed with the modified coherence-power-weighted EMI algorithm, and the optimal phase history is retrieved. The experimental results validated against both simulated and Sentinel-1A data demonstrate the superior optimization performance and robustness of the adaptive POA over traditional POAs.

Integrating RELAX with PS-InSAR Technique to Improve Identification of Persistent Scatterers for Land Subsidence Monitoring

Identifying Persistent Scatterers (PSs) is one of the key processing steps of the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique. The number, density, and reliability of identified PSs directly affect the monitoring accuracy of land subsidence, especially in higher density urban environments. As a result of the side-looking viewing geometry of SAR, the layover effect poses a major challenge to the PS identification. This research proposes joint modeling of the PS-InSAR technique and RELAX algorithm for SAR tomography (PS-InSAR+RELAX) to detect single and double scatterers and to improve the identification and reliability of PSs. It has been demonstrated that RELAX improves separation of the scatterers when compared to two other spectral analysis methods for SAR tomography, Beam-Forming (BF) and Singular Value Decomposition (SVD). RELAX exhibits the least noise when the number of baseline changes from 15 to 30, and it can separate the scatterers at a lower Normal-Slant-Range (NSR) height than the two other methods. As RELAX can better identify, separate, and then filter out layover scatterers, the number and density of PSs identified by PS-InSAR+RELAX is reduced and visually simplified, suggesting that the method can effectively reduce the influence of the layover effect on the PS identification. Also, the PSs identified by PS-InSAR+RELAX are more coherent than those identified by the traditional PS-InSAR technique. The proposed technique has been applied to Sentinel-1A data acquired from 2014 to 2016, to monitor land subsidence in the city of Beijing, China. When evaluated against the leveling measurements, PS-InSAR+RELAX performs better than the traditional PS-InSAR technique, with the correlation coefficients (r) of r = 0.98 and r = 0.95, respectively.

Extreme subsidence in a populated city (Mashhad) detected by PSInSAR considering groundwater withdrawal and geotechnical properties

Ground deformation can cause serious environmental issues such as infrastructure damage, ground compaction, and reducing the ground capacity to store water. Mashhad, as one of the largest and most populated cities in the Middle East, has been suffering from extreme subsidence. In the last decade, some researchers have been interested in measuring land subsidence rates in the Mashhad valley by InSAR techniques. However, most of those studies were based on inaccurate measurements introducing uncertainties in the resulting subsidence rates. These researches used a small number of EnviSat data with long perpendicular and inhomogeneous temporal baseline. This paper seeks to determine the subsidence rate in urban areas of Mashhad in recent years, the threat that was neglected by the city managers and decision-makers. For this purpose, the Persistent Scatterer InSAR technique was applied in the study area using two time-series of descending and ascending Sentinel-1A acquisitions between 2014 and 2017. The results demonstrated the maximum line-of-sight deformation rate of 14.6 cm/year and maximum vertical deformation (subsidence) rate about 19.1 cm/year which could have irreversible consequences. The results were assessed and validated using piezometric data, GPS stations, and geotechnical properties. This assessment confirms that the main reason for subsidence in the interested area is groundwater over-extraction. Also, investigation of geotechnical properties shows that thick fine-grained layers in the northwest of the city could strongly affect the results. At the end of this paper, a new simplified method was proposed to estimate specific storage in special cases to predict the subsidence rate.

PSInSAR Study of Lyngenfjord Norway, using TerraSAR-X Data

Abstract. In this research paper, focus is given on exploring the potential of Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique for the measurement of landslide, which is the extension of existing DInSAR technique. In PSInSAR technique, the movement is measured by finding the phase shift in the scatterers present in the study area through the course of time. The backscattering of such a scatterer does not change during the study. By using this technique, 32 datasets acquired over a period of time i.e. from 2009 to 2011 over the area of Troms County of Lyngen Fjord, Norway are analysed. The dataset utilised are acquired with TerraSAR-X and TanDEM-X pair, in Stripmap mode of acquisition. Coregistration of dataset with subpixel accuracy is done with master images is done to align all the dataset correctly. APS estimation is done in order to remove the phase decorrelation caused by the atmosphere, movement, etc. using algorithms for phase unwrapping which allowed the processing of sparse data and the effect of atmosphere is reduced by doing analysis on temporal basis of the phase shift in interferograms of successive datasets. By this study it has been tried to show the estimation of shift can be done by the temporal analysis of the data acquired by TerraSAR-X. The velocity output is displayed in a map reflecting the velocity of movement. Apart from this, the data properties such as baseline distribution both temporal and spatial are displayed in a chart. Other outputs obtained are the atmospheric Phase Screen, sparse point distribution, reflectivity map of the study area etc. are displayed using a map of terrain. The output velocity obtained of the terrain movement is found to be in the range of −40 mm/yr to −70 mm/yr.

A hybrid clustering-fusion methodology for land subsidence estimation

A hybrid clustering-fusion methodology is developed in this study that employs genetic algorithm (GA) optimization method, k-means method, and several soft computing (SC) models to better estimate land subsidence. Estimation of land subsidence is important in planning and management of groundwater resources to prevent associated catastrophic damages. Methods such as the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) can be used to estimate the subsidence rate, but PS-InSAR does not offer the required efficiency and accuracy in noisy pixels (obtained from remote sensing). Alternatively, a fusion-based methodology can be used to estimate subsidence rate, which offers a superior accuracy as opposed to the traditionally used methods. In the proposed methodology, five SC methods are employed with hydrogeological forcing of frequency and thickness of fine-grained sediments, groundwater depth, water level decline, transmissivity and storage coefficient, and output of land subsidence rate. Results of individual SC models are then fused to render more accurate land subsidence rate in noisy pixels, for which PS-InSAR cannot be effective. We first extract 14,392 different input–output patterns from PS-InSAR technique for our study area in Tehran province, Iran. Then, k-means method is used to divide the study area into homogenous zones with similar features. The five SC models include adaptive neuro fuzzy inference system, support vector regression, multilayer perceptron neural network and two optimized models, namely radial basis function and generalized regression neural network. To fuse individual SC models, three methods including GA, K-nearest neighbors and ordered weighted average (OWA) based on ORNESS method and ORLIKE method, are developed and evaluated. Results show that the fusion-based method is significantly superior to each of the employed individual methods in predicting land subsidence rate.

Using PS-InSAR to detect surface deformation in geothermal areas of West Java in Indonesia

In this paper, the Persistent Scatterer InSAR (PS-InSAR) technique is applied in order to investigate the ground deformation in and around two geothermal areas in West Java, Indonesia. Two time-series of ALOS PALSAR and Sentinel-1A acquisitions, covering the period from 2007 to 2009 and 2015–2016, are analysed. The first case study examines the Wayang Windu geothermal zone where the PS-InSAR analysis provides an overview of the surface deformation around a geothermal reservoir. Uplift is observed around the injection wells in the area. The second example involves the use of the PS-InSAR technique over a more recent geothermal system in Patuha field. Again, a pattern of uplift was observed around the only available injection well in the area. Due to the dense vegetation coverage of the geothermal areas in West Java, the longer wavelength ALOS PALSAR data is provides better results by identifying a larger number of PS points. Additionally, experiments have been carried out to compare the resulting deformation with another example of the fluid migration process i.e. water extraction in Bandung basin. The potential of sentinel-1A and ALOS PALSR data are compared in all the experiments.

The effectiveness of high-resolution LiDAR data combined with PSInSAR data in landslide study

The spatial resolution of digital elevation models (DEMs) is an important factor for reliable landslide studies. Multi-interferometric techniques such as persistent scatterer interferometric synthetic aperture radar (PSInSAR) are used to evaluate the landslide state of activity and its ground deformation velocity, which is commonly measured along the satellite line of sight (LOS). In order to compare velocities measured by different satellites in different periods, their values can be projected along the steepest slope direction, which is the most probable direction of real movement. In order to achieve this result, DEM-derived products are needed. In this paper, the effectiveness of different DEM resolutions was evaluated in order to project ground deformation velocities measured by means of PSInSAR technique in two different case studies in the Messina Province (Sicily, southern Italy): San Fratello and Giampilieri. Three DEMs were used: (i) a 20-m resolution DEM of the Italian Military Geographic Institute (IGM), (ii) a 2-m resolution DEM derived from airborne laser scanning (ALS) light detection and ranging (LiDAR) data for the San Fratello 2010 landslide, and (iii) a 1-m resolution DEM derived from ALS LiDAR data for the area of Giampilieri. The evaluation of the applied method effectiveness was performed by comparing the DEMs elevation with those of each single permanent scatterer (PS) and projecting the measured velocities along the steepest slope direction. Results highlight that the higher DEM resolution is more suitable for this type of analysis; in particular, the PS located nearby the watershed divides is affected by geometrical problems when their velocities are projected along the steepest slope.

Application of Differential SAR Interferometry in Mining Subsidence Monitoring

Differential synthetic aperture radar Interferometry has been widely applied to monitor mining subsidence for its high spatial resolution, competent accuracy and wide coverage. In this paper, we introduce the principles of InSAR, discuss several key technical issues in mining subsidence monitoring, including selection of SAR images, advanced algorithms for phase unwrapping and Persistent Scatterer InSAR technique.

Analysis and Detection of Groundwater Exploitation-Induced Urban Deformation Disaster Based on PS-InSAR and GIS

AbstractInterferometric synthetic aperture radar (InSAR) is a very effective technique for measuring surface deformation, but the temporal and geometrical decorrelation and atmospheric disturbances can compromise strongly the accuracy of the results. Persistent scatterer InSAR (PS-InSAR) overcomes the decorrelation and atmospheric disturbances problem. The results obtained by PS-InSAR technique are not the field deformation information but persistent scatterers deformation. In this paper, PS-InSAR and geographic information system (GIS) are used to investigate surface deformation caused by groundwater overexploitation in Nantong, China. For improving the accuracy of extracting the atmospheric effects in the PS-InSAR technique, an automatic determining method of the best filter method and filter window size is proposed when extracting the atmospheric effects from the residual phase by filtering. The proposed method is based on structure function of residual phases. The linear deformation rate of permanent ...

Estimating Spatiotemporal Ground Deformation With Improved Persistent-Scatterer Radar Interferometry$^\ast$

Synthetic aperture radar interferometry has been applied widely in recent years to ground deformation monitoring although difficulties are often encountered when applying the technology, among which the spatial and temporal decorrelation and atmospheric artifacts are the most prominent. The persistent-scatterer interferometric synthetic aperture radar (PS-InSAR) technique has overcome some of the difficulties by focusing only on the temporally coherent radar targets in a time series of synthetic aperture radar (SAR) images. This paper presents an improved PS-InSAR technique by introducing PS-neighborhood networking and empirical mode decomposition (EMD) approaches in the PS-InSAR solution. Linear deformation rates and topographic errors are estimated based on a least squares method, while the nonlinear deformation and atmospheric signals are computed by singular value decomposition and the EMD method. An area in Phoenix, AZ, is used as a test site to determine its historical subsidence with 39 C-band SAR images acquired by European Remote Sensing 1 and 2 satellites from 1992 to 2000.